Early Prediction of Post-Cesarean Infection Using Preoperative and Postoperative Hematologic Markers: A Case-Control Study

Background: Postoperative infections remain a significant complication following cesarean delivery, highlighting the need for reliable and accessible methods for early detection. This study aimed to evaluate the predictive value of preoperative and postoperative systemic inflammation markers for post-cesarean section infections. Methods: This case-control study included women admitted to the maternity ward of Niğde Ömer Halisdemir University Hospital between 1 October 2021, and 1 October 2023. 50 patients who developed infections following cesarean sections (CS) were compared with 50 control patients. Demographic, clinical, and obstetric information was collected from hospital records. Complete blood count (CBC) results collected 3–10 days prior to surgery and 24 hours post-surgery were analyzed and compared between the two study groups. Results: Among patients in the study group, 84% developed surgical site infection (SSI), while the remaining 16% experienced other types of infections. No significant differences were observed between the groups in terms of maternal age, body mass index (BMI), birth weight, length of surgery, blood loss, gestational age at delivery, smoking history, gestational diabetes mellitus, hypertensive disorders of pregnancy, intensive care unit admission, history of emergency CS, gravidity, and parity (p > 0.05). No significant differences were observed between preoperative and postoperative values for platelet count (PLT), mean platelet volume (MPV), mean platelet volume-to-platelet ratio (MPV/PLT), or platelet-to-lymphocyte ratio (PLR) (p > 0.05). Postoperative monocyte-to-lymphocyte ratio (MLR) and neutrophil-to-lymphocyte ratio (NLR) were significantly in patients with post-CS infections; receiver operating characteristic (ROC) analysis was used to determine optimal cut-off values (p < 0.001). Conclusions: NLR and MLR may serve as reliable, simple, and effective biomarkers to enhance clinical decision-making for the early detection and prediction of post-cesarean infections.